With the expeditious development of web technology, various kinds of web sites or web applications have sprung up. In the web service field, web analytics needs to be performed so as to better understand and analyze information related to users' access to web sites and pages of the websites. Web analytics provides a series of analytical results through analyzing the actions of users' access to pages, which, by using the analytical results, may conveniently and intuitively understand the trend of users' access to web pages. Specifically, the analytical results may comprise clicking path information related to visitors' page access sequences inside a website, and with this information, a website technician may better organize and adjust the page structure and content arrangement inside the website.
In a traditional Web 1.0 environment, web analytics tools, such as Google® Analytics, and Web Trends®, usually perform data statistical analysis on the user's access data per page because, in the Web 1.0 environment, a user's clicking operation on a page will cause a jump of the page (i.e., a change of the URL address).
However, the above web analytics methods or tools applicable in the Web 1.0 environment are not applicable in the Web 2.0 environment because in the Web 2.0 environment, Asynchronous JavaScript® and XML (Ajax) technology, which is a web development technology creating an interactive web application, is widely used. As a result, many operations may be performed when a user visits a website in the Web 2.0 environment which do not require a jump of the page (i.e., no change to the URL address). Therefore, many operations in a Web 2.0 website are performed based on dynamic page elements and not based on pages. If the web analytics methods or tools in a traditional Web 1.0 environment are still used, it would be impossible to correctly collect, in the Web 2.0 website, data information related to users' access operations in the website. From another perspective, many different pages inside a website may actually have page elements with a similar structure or content. For example, in a portal website, there are dozens or even hundreds of subpages under the news column, which comprise news page elements with similar structures. If user access analytics is still performed based upon page jump in a traditional manner, it would be impossible to make statistics on users' visit traffic and visit habits on the news column. In other words, to perform web analytics in a Web 2.0 website, more hybrid data must be collected to mine meaningful information therein. It also provides a bigger challenge for data collection, data visualization, and information filtering during a web analytics process.